INVOICE PROCESSING

Normalize S3-dropped vendor invoices to base currency before Snowflake load

Watches an S3 bucket for new vendor invoice files, converts each invoice total to your reporting currency at the invoice date's FX rate.

CategoryInvoice Processing
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew invoice file lands in S3 bucketAWS S3
  • ActionRead and parse vendor, currency, amount, dateAWS S3
  • ActionFetch FX rate for invoice-date currency pairHTTP webhook
  • LogicCompute base-currency total; flag missing rates
  • OutputInsert normalized row into Snowflake staging tableSnowflakeSnowflake

What it does

When finance receives multi-currency vendor invoices into an S3 bucket, this workflow reads each file, looks up the FX rate for the invoice date, computes the base-currency amount, and writes a clean normalized record to a Snowflake staging table that your ERP picks up.

When to use it

Use it when vendors email or upload invoices that land in S3 across many currencies (EUR, GBP, JPY, etc.) and your ledger only accepts a single reporting currency. It removes manual FX lookups and keeps every staged row auditable with the rate used.

How it works

  1. 1An S3 object-created event fires when a new invoice file lands in the watched prefix.
  2. 2The file is read and parsed to extract vendor, currency, original amount, and invoice date.
  3. 3An HTTP call fetches the daily FX rate for that currency pair on the invoice date.
  4. 4A logic step computes base-currency total and flags any invoice missing a rate.
  5. 5The normalized row, including original amount, rate, and converted total, is inserted into the Snowflake staging table for ledger import.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AWS S3Buckets, objects, signed URLs.
  2. 2
    Connect HTTP webhookTrigger any URL on agent actions.
  3. 3
    Connect SnowflakeWarehouses, queries, shares.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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